We are proposing a predoctoral training program in Biostatistics in Genetics, Immunology, and Neuroimaging (BGIN). In this program, students will learn to develop statistical and computational innovations applied in one of three areas of concentration: 1. genetics /genomics, 2. immunology/ vaccinology/infectious diseases, or 3. neuroimaging. The rationale for this program at Emory is the strong interdisciplinary research programs already in place in these areas. Emory also has a stong multidisciplinary Graduate Division of Biological and Biomedical Sciences with eight integrated PhD programs. This BGIN program will take advantage of the already existing strong degree program in Biostatistics and the related degree programs in the biological sciences. The BGIN program consists of three cores (1) biostatistics, (2) scientific concentration, and (3) (optional) computer science/database management. The students will take electives in their area of scientific concentration as well as additional electives in biostatistics. The program leadership consists of representatives from biostatistics, genetics, and neuroimaging. The 22 program faculty are from Biostatistics and four other PhD programs in the Graduate Division of Biological and Biomedical Sciences at Emory. The program will recruit two new students each year [unreadable] with stipend support for three years, for a total of 24 slots over the five years. [unreadable] [unreadable] Year 1 2 3 4 5 [unreadable] Number of students 2 4 6 6 6 [unreadable] [unreadable] The training facilities will include the Department of Biostatistics, the Emory Vaccine Research Center, the Emory neuroimaging facilities, the Department of Human Genetics, the Center for Genomics and Disease Prevention of the National Center for Diseases Control and Prevention, Georgia Tech, among others. The goal of the program is to produce biostatisticians who are knowledgeable in their applied field of bioscience with the ability to further the science and insight with new statistical methods. [unreadable] [unreadable] [unreadable]